docs: def get_mean_and_stddevs(self, sites, rup, dists, imt, stddev_types):
          """
          See :meth:`superclass method
          <.base.GroundShakingIntensityModel.get_mean_and_stddevs>`
          for spec of input and result values.
          """
          # extracting dictionary of coefficients specific to required
          # intensity measure type.
          C = self.COEFFS[imt]
  
          mean = (self.get_magnitude_scaling(C, rup.mag) +
                  self.get_distance_term(C, rup, dists.rjb, imt) +
                  self.get_site_amplification(C, sites))
          # GMPE originally in cm/s/s - convert to g
          if imt.name in "PGA SA":
              mean -= np.log(100.0 * g)
          stddevs = self.get_stddevs(C, dists.rjb.shape, stddev_types, sites)
          if self.sigma_mu_epsilon:
              # Apply the epistemic uncertainty factor (sigma_mu) multiplied by
              # the number of standard deviations
              sigma_mu = self.get_sigma_mu_adjustment(C, imt, rup, dists)
              # Cap sigma_mu at 0.5 ln units
              sigma_mu[sigma_mu > 0.5] = 0.5
              # Sigma mu should not be less than the standard deviation of the
              # fault-to-fault variability
              sigma_mu[sigma_mu < C["tau_fault"]] = C["tau_fault"]
              mean += (self.sigma_mu_epsilon * sigma_mu)
          return mean, stddevs